Covid Report for Family

Background

Notes and format last updated May 7, 2020

Starting on the May 7th update, the NY Times began including probable covid cases/deaths along with confirmed. This mostly affects death counts – for certain geographies that include probable COVID deaths in addition to confirmed, these are now added to the totals. For the time being, they were all added to the May 6th totals, causing a big spike at the U.S. level. Over time, NY Times will revise their historical counts and distribute these added deaths when they actually occurred, so the spike should fade.

• This page shows COVID data broken down into regions that affect our family. It pulls from publicly available raw data from the NY Times, which is reported daily. It’s on a one-day lag, so when you see this report, the most recent day included will be that reported the day prior.
• The table of contents above summarizes the major sections and can be used to jump to those sections.
• Each major section is then divided into tabs to allow you to more easily shuffle between geographies and metrics.
  • If you open on your phone, I don’t believe the tabs will work, so you’ll just see the page as one long, continuous document.
• More detailed descriptions and context can be found in each section.

Growth rates

Heat maps

• The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
• The first plot compares growth rate for total cases; the second, growth rate for total deaths.
• The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
• The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
  • You can use the plots to track each geography over time and to compare the geographies to one another.
  • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
  • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
  • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

• This section charts the growth rate of both total and new deaths for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total deaths and new deaths.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
  • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
  • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

• This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
• For each metric, in addition to the tables, the trends for the top states are plotted over time.
  • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)

Ranking	State	Cases Per Million
1	North Dakota	144,776
2	Rhode Island	143,627
3	South Dakota	140,521
4	Utah	127,418
5	Tennessee	124,480
6	Arizona	121,593
7	Iowa	117,984
8	Wisconsin	116,101
9	Nebraska	115,649
10	South Carolina	115,480
11	Oklahoma	114,757
12	New Jersey	114,666
13	Arkansas	113,634
14	Delaware	112,167
15	Indiana	111,573
16	Alabama	111,528
17	Illinois	109,718
18	Kansas	108,863
19	Florida	108,477
20	New York	108,232
21	Idaho	108,208
22	Mississippi	107,079
23	Minnesota	106,963
24	Nevada	106,028
25	Montana	105,446
26	Wyoming	105,295
27	Georgia	103,862
28	Kentucky	103,554
29	Massachusetts	102,786
30	Texas	102,485
31	Louisiana	102,102
32	Missouri	100,960
33	Michigan	99,560
34	Connecticut	97,681
35	New Mexico	97,205
36	California	96,147
37	North Carolina	96,067
38	Colorado	95,760
39	Alaska	95,693
40	Pennsylvania	94,632
41	Ohio	94,594
42	West Virginia	90,799
43	Virginia	79,340
44	Maryland	76,265
45	New Hampshire	72,806
46	District of Columbia	69,609
47	Washington	58,323
48	Puerto Rico	54,093
49	Maine	50,872
50	Oregon	48,370
51	Vermont	38,942
52	Hawaii	25,045

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Cases Per Million
1	Wyoming	183
2	Texas	161
3	Nevada	128
4	Louisiana	119
5	Montana	103
6	Washington	98
7	Idaho	94
8	Missouri	94
9	Colorado	91
10	West Virginia	91
11	Alabama	85
12	Utah	81
13	Kentucky	69
14	North Carolina	68
15	Indiana	61
16	Kansas	60
17	Oregon	60
18	Arizona	55
19	Mississippi	55
20	New Mexico	55
21	Arkansas	54
22	Alaska	53
23	Rhode Island	50
24	Oklahoma	45
25	North Dakota	43
26	Georgia	40
27	Maine	37
28	Michigan	37
29	Wisconsin	36
30	Connecticut	34
31	Delaware	33
32	Pennsylvania	33
33	Tennessee	33
34	Ohio	30
35	New Hampshire	29
36	South Carolina	28
37	District of Columbia	27
38	Illinois	27
39	Minnesota	27
40	California	26
41	Nebraska	26
42	Vermont	25
43	New York	24
44	Hawaii	23
45	Iowa	23
46	New Jersey	22
47	South Dakota	19
48	Massachusetts	18
49	Virginia	18
50	Maryland	15
51	Puerto Rico	14
52	Florida	0

Total deaths

Table of total deaths per million residents (all 50 states)

Ranking	State	Deaths Per Million
1	New Jersey	2,961
2	New York	2,720
3	Massachusetts	2,600
4	Rhode Island	2,569
5	Mississippi	2,468
6	Arizona	2,433
7	Connecticut	2,315
8	Alabama	2,294
9	Louisiana	2,286
10	South Dakota	2,286
11	Pennsylvania	2,145
12	Michigan	2,067
13	New Mexico	2,047
14	Indiana	2,036
15	North Dakota	2,031
16	Illinois	2,005
17	Arkansas	1,939
18	Iowa	1,928
19	Georgia	1,919
20	South Carolina	1,895
21	Oklahoma	1,851
22	Nevada	1,823
23	Tennessee	1,814
24	Texas	1,792
25	Kansas	1,763
26	Delaware	1,722
27	Florida	1,721
28	Ohio	1,712
29	District of Columbia	1,611
30	California	1,609
31	Kentucky	1,603
32	Maryland	1,597
33	Missouri	1,593
34	West Virginia	1,588
35	Montana	1,530
36	Wisconsin	1,373
37	Minnesota	1,342
38	Virginia	1,319
39	Nebraska	1,300
40	North Carolina	1,263
41	Wyoming	1,252
42	Idaho	1,185
43	Colorado	1,179
44	New Hampshire	998
45	Puerto Rico	790
46	Washington	766
47	Utah	723
48	Oregon	651
49	Maine	627
50	Alaska	481
51	Vermont	410
52	Hawaii	354

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Deaths Per Million
1	West Virginia	6
2	Alabama	3
3	Colorado	2
4	Idaho	2
5	Kansas	2
6	Michigan	2
7	Mississippi	2
8	Missouri	2
9	North Carolina	2
10	Oregon	2
11	Wisconsin	2
12	Wyoming	2
13	Connecticut	1
14	Georgia	1
15	Illinois	1
16	Indiana	1
17	Iowa	1
18	Kentucky	1
19	Louisiana	1
20	Montana	1
21	Nevada	1
22	New Jersey	1
23	New Mexico	1
24	Ohio	1
25	Pennsylvania	1
26	Rhode Island	1
27	Texas	1
28	Alaska	0
29	Arizona	0
30	Arkansas	0
31	California	0
32	Delaware	0
33	District of Columbia	0
34	Florida	0
35	Hawaii	0
36	Maine	0
37	Maryland	0
38	Massachusetts	0
39	Minnesota	0
40	Nebraska	0
41	New Hampshire	0
42	New York	0
43	North Dakota	0
44	Oklahoma	0
45	Puerto Rico	0
46	South Carolina	0
47	South Dakota	0
48	Tennessee	0
49	Utah	0
50	Vermont	0
51	Virginia	0
52	Washington	-1

Counties

• This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
  • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
• In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Cases Per Million	Raw Ranking	Percentile
Chattahoochee	Georgia	394,517	1	99
Crowley	Colorado	364,461	2	99
Bent	Colorado	276,851	3	99
Maverick	Texas	260,924	4	99
Dewey	South Dakota	250,339	5	99
Davidson	Tennessee	143,289	191	93
Richland	South Carolina	113,737	998	68
York	South Carolina	113,688	1000	68
Orange	California	85,824	2265	27
Pierce	Washington	61,857	2828	9

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Deaths Per Million	Raw Ranking	Percentile
Foard	Texas	8,658	1	99
Galax city	Virginia	8,350	2	99
Hancock	Georgia	8,041	3	99
Jerauld	South Dakota	7,948	4	99
Emporia city	Virginia	7,856	5	99
Orange	California	1,603	1857	40
York	South Carolina	1,384	2109	32
Richland	South Carolina	1,381	2112	32
Davidson	Tennessee	1,373	2126	32
Pierce	Washington	734	2773	11

Our county percentiles over time

Raw counts

• This section shows the raw counts over time for the U.S., our states, and our counties for four categories:
  • Total confirmed cases: This is the cumulative total of cases reported.
  • New confirmed cases: This is the number of new cases reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new cases, to help better visualize the peak.
  • Total deaths: This is the cumulative total of deaths reported.
  • New deaths: This is the number of new deaths reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new deaths, to help better visualize the peak.

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons

• This section is a work in progress. It’s exploring what effect stay-at-home orders have on spread. It’s inherentely messy because some states have localized orders but not orders for their full state and because states implemented the orders at different times.
  • The first plot shows a rolling 3-day average of new cases per million residents, averaged across 2 groups of states – those with a state-wide stay-at-home order in effect and those without. The size of the dots reflect the number of states in each group for each given day (so the dots are getting bigger over time for the group with orders, as more states implement those orders).
    • So far, this view doesn’t show if these orders are “working” or not. Instead, the biggest takeaway from the current plot is that the states that implemented orders are reacting to having worse spread, which is why the case rate is so much higher at the start for them. As a state decides it has a problem and implements an order, it joins the grouping of states with orders and drives the rate up for that group.
    • Over time (if the policies work), what we’d expect is that the line for the group with orders flattens or declines in relation to the no-order group. It also may become moot if all states issue orders.
    • As states start rescending their orders, I’ll put them back into the no-order group, so the no-order group should beging to expand again.
  • The second plot tracks progress of states by the number of days since orders have been in effect. It includes only those states with orders and shows their average new case growth rate (a rolling 3-day average of daily growth rates) based on how long it’s been since the order went into effect. Again, the size of the dots show how many states are included in each point – i.e., as you go further right, the dots are smaller because less states are that far past their order.
    • I’m working on how to add a baseline to this chart to compare to states without orders, but that’s challenging because there’s no way to fully align timing.